Large-scale hydropower engineering reservoir bank geological disaster identification method and device

Abstract

The invention relates to the technical field of geological disaster recognition, in particular to a large-scale hydropower engineering reservoir bank geological disaster recognition method and device.In the early stage of water storage, an unmanned aerial vehicle photogrammetry system is controlled to collect multiple images of a current hydropower engineering reservoir bank area, and the multiple images are analyzed and processed; constructing a three-dimensional real scene model of the current reservoir area by using the processed image; geological disaster hidden danger points in the three-dimensional real scene model of the current reservoir area are identified and marked, and all the geological disaster hidden danger points are determined; and carrying out water storage period dynamic identification, and determining a target geological disaster hidden danger point in the geological disaster hidden danger points. By monitoring and identifying possible disaster types in the hydropower engineering reservoir bank area in the early stage of water storage and dynamically identifying specific disaster types in the water storage period, hidden danger can be found in advance, and the accuracy of geological disaster identification is effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of geological disaster identification, and in particular to a method and device for identifying geological disasters on the reservoir bank of a large hydropower project. Background Art

[0002] The southwestern mountainous areas of my country are a key area for domestic water conservancy and hydropower construction, with well-developed valleys, crisscrossing rivers, and crisscrossing rivers and rivers. On the one hand, the construction of these water conservancy projects has eased the power shortage in my country and provided impetus for the development of the national economy. On the other hand, since the southwestern mountainous areas are located in the Hengduan Mountains on the eastern edge of the Qinghai-Tibet Plateau, many fault zones intersect in them, resulting in active tectonic activities in the region, which also causes frequent geological disasters in the region. The construction and operation of reservoirs are bound to change the original geological environment, aggravate the scale and frequency of geological disasters on the bank slopes, and lead to the occurrence of new geological disasters such as collapse, landslides, and mud-rock flows, and even the revival or partial revival of ancient landslides, which brings great safety risks and economic losses.

[0003] For a long time, the focus of geological disaster prevention and control in hydropower projects has been concentrated in the field of disaster management, and good management results have been achieved. However, we need to realize that even if a lot of manpower, material and financial resources are spent on engineering management, the frequent, easy and sudden occurrence of bank slope geological disasters has not changed. The disaster source area is located in the middle and upper parts of the mountains. Most areas are rarely visited and covered by vegetation. They are high and hidden. Traditional manual inspections and group monitoring and prevention are powerless in the face of such disasters. Traditional means are difficult to detect such disaster hazards in advance. Many sudden disasters are not in the hidden danger database, and it is impossible to effectively identify geological disasters during the operation period of hydropower projects, resulting in a passive situation in the prevention and control of geological disasters during the operation period of hydropower projects. Summary of the invention

[0004] The purpose of the present invention is to provide a method and device for identifying geological disasters on the reservoir bank of a large hydropower project, so as to solve the problem that the existing geological disasters during the operation period of the hydropower project cannot be effectively identified.

[0005] In order to solve the above technical problems, in a first aspect, the present invention provides a method for identifying geological disasters on the reservoir bank of a large hydropower project, comprising the following steps: In the early stage of water storage, the UAV photogrammetry system is controlled to collect multiple images of the reservoir bank area of ​​the current hydropower project, the multiple images are analyzed and processed, and a three-dimensional real scene model of the current reservoir area is constructed using the processed images; Identify and mark the geological disaster risk points in the 3D real-life model of the current reservoir area and determine each geological disaster risk point; Dynamic identification is performed during the water storage period to determine the target geological disaster risk points among the various geological disaster risk points.

[0006] In combination with the first aspect above, in some possible implementations, analyzing and processing the multiple images includes: The multiple images are sequentially stitched, aerially triangulated, orthorectified, and mosaicked to obtain a processed image.

[0007] In combination with the first aspect above, in some possible implementations, the aerial triangulation includes determining exterior orientation elements of all images in the area using a photogrammetric analysis method.

[0008] In combination with the first aspect above, in some possible implementations, the orthorectification includes: The image is divided into multiple sub-areas, and digital differential correction is performed one by one. According to the digital ground model, the coordinates are solved using the corresponding image equations. Import the aerial triangulated images and the DEM generated after point cloud classification into the corresponding software. The DEM needs to cover the image area, perform orthorectification on the image, and generate a single image after orthorectification.

[0009] In combination with the first aspect, in some possible implementations, the mosaic fusion includes: The digital image mosaic technology is used to stitch together multiple orthorectified images with overlapping areas taken under the same or different imaging conditions into a complete image.

[0010] In combination with the first aspect above, in some possible implementations, using the processed images to construct a three-dimensional real scene model of the current reservoir area includes: Context Capture oblique photography post-processing software was used to analyze the acquired processed images and exclude defective images; Use the remaining images to construct a three-dimensional real-life model of the current reservoir area.

[0011] In combination with the first aspect above, in some possible implementations, the geological disaster risk points in the three-dimensional real-life model of the current reservoir area are identified and marked to determine the geological disaster risk points, including: The EarthSurvey software platform is used to identify and mark the geological disaster risk points in the three-dimensional real-scene model to obtain each geological disaster risk point.

[0012] In combination with the first aspect above, in some possible implementations, dynamic identification during the water storage period is performed to determine the target geological disaster risk point among the various geological disaster risk points, including: Conduct dynamic risk assessment of the reservoir area during the impoundment period; Based on the results of the dynamic hazard assessment of the reservoir area, detailed drone verification is carried out to determine the target geological disaster risk points among the various geological disaster risk points.

[0013] In combination with the first aspect above, in some possible implementations, a dynamic hazard assessment of the reservoir area is performed, including: determining extremely high-risk slopes and high-risk slopes.

[0014] To solve the above technical problems, in a second aspect, the present invention also provides a device for identifying geological hazards on the reservoir bank of a large hydropower project, comprising a memory, a processor, and an executable computer program stored in the memory and run on the processor, wherein when the processor executes the computer program, a method for identifying geological hazards on the reservoir bank of a large hydropower project in the above first aspect or any possible implementation of the first aspect is executed.

[0015] The present invention has the following beneficial effects: by controlling the drone photogrammetry system to collect multiple images of the reservoir bank area of ​​the current hydropower project in the early stage of water storage, the multiple images are analyzed and processed, and the processed images are used to construct a three-dimensional real-scene model of the current reservoir area; the geological disaster risk points in the three-dimensional real-scene model of the current reservoir area are identified and marked, and each geological disaster risk point is determined; dynamic identification is performed during the water storage period to determine the target geological disaster risk point among the various geological disaster risk points. The present invention uses drone technology to monitor the reservoir bank area of ​​the hydropower project in the early stage of water storage to identify possible disaster types, and dynamically identifies specific disaster types during the water storage period, discovers disaster risks in advance, effectively improves the accuracy of geological disaster identification, and converts passive disaster management into active prevention and control, thereby reducing the loss of life and property. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 A schematic diagram of the basic flow of a method for identifying geological hazards on the reservoir bank of a large hydropower project according to an embodiment of the present invention; Figure 2 A schematic structural diagram of an unmanned aerial vehicle photogrammetry system according to an embodiment of the present invention; Figure 3 A schematic diagram of route settings according to an embodiment of the present invention; Figure 4 The present invention is a schematic structural diagram of a large-scale hydropower project reservoir bank geological disaster identification device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0018] In order to clearly illustrate the technical features of the present invention, the present invention is described in detail below through specific implementation methods in conjunction with the accompanying drawings.

[0019] Embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be construed as being limited to the embodiments described herein, which are instead provided for a more thorough and complete understanding of the present invention. It should be understood that the drawings and embodiments of the present invention are only for exemplary purposes and are not intended to limit the scope of protection of the present invention.

[0020] It should be understood that the various steps described in the method embodiments of the present invention may be performed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present invention is not limited in this respect.

[0021] The term "including" and its variations used herein are open inclusions, i.e., "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the following description.

[0022] It should be noted that the concepts such as "first" and "second" mentioned in the present invention are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0023] Although operations or steps are described in a specific order in the drawings in the embodiments of the present invention, it should not be understood that it is required to perform these operations or steps in the specific order shown or in a serial order, or that all the operations or steps shown must be performed to obtain the desired results. In the embodiments of the present invention, these operations or steps may be performed in series; these operations or steps may also be performed in parallel; or some of these operations or steps may be performed.

[0024] At the same time, it is understood that the data involved in the technical solution of the present invention (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of the relevant laws, regulations and relevant provisions. Unless otherwise defined, all technical and scientific terms used in the present invention have the same meanings as those generally understood by technicians in the technical field of the present invention, and all parameters or indicators in the formulas involved in the present invention are normalized values ​​that eliminate the influence of dimensions.

[0025] In order to solve the problem that geological disasters during the operation period of hydropower projects cannot be effectively identified, an embodiment of the present invention provides a method and device for identifying geological disasters on the reservoir bank of a large hydropower project. By monitoring the reservoir bank area of ​​the hydropower project in the early stage of water storage to identify possible disaster types, and dynamically identifying specific disaster types during the water storage period, potential disaster risks are discovered in advance, and passive disaster management is converted into active prevention and control, thereby reducing the loss of life and property.

[0026] A method and device for identifying geological hazards on the reservoir bank of a large hydropower project provided by an embodiment of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0027] Figure 1 FIG. 1 is a schematic diagram showing a basic flow chart of a method for identifying geological hazards on the reservoir bank of a large hydropower project provided by an embodiment of the present invention. Figure 1 As shown, the method specifically comprises the following steps: Step S100: In the early stage of water storage, the UAV photogrammetry system is controlled to collect multiple images of the reservoir bank area of ​​the current hydropower project, the multiple images are analyzed and processed, and a three-dimensional real scene model of the current reservoir area is constructed using the processed images.

[0028] Synthetic Aperture Radar Interferometry (InSAR) technology can monitor deformation of a large area of ​​the study area as a whole, but due to the poor timeliness of remote sensing images and the interference of clouds, it is impossible to obtain a digital elevation model (DEM) and conduct subsequent topographic analysis. UAV photogrammetry technology can fill the gap in InSAR satellite monitoring, and can also use UAV data to review and verify InSAR deformation during the water storage period. Carrying out UAV deformation monitoring of large slope deformation can effectively make up for the shortcomings of InSAR in monitoring sudden disasters. UAV photogrammetry technology is combined with InSAR technology, and a spatial basic database and multi-source data fusion platform for the reservoir area are established to manage basic geology, geological disasters and InSAR deformation monitoring results, providing effective technical support for the safety and stability of the reservoir area during the water storage period.

[0029] UAV photogrammetry technology can obtain high-definition stereo image data through ultra-low-altitude photography, and with the help of control points or image POS information, it can obtain centimeter-level measurement accuracy and automatically generate three-dimensional geographic information models, quickly acquiring geographic information. It has the advantages of high efficiency, low cost, accurate data, flexible operation, and available side information.

[0030] Control the UAV photogrammetry system to collect multiple images of the reservoir bank area of ​​the current hydropower project. Figure 2The structure diagram of a UAV photogrammetry system provided by an embodiment of the present invention is shown. The UAV photogrammetry system is composed of a flight platform, a mission payload and its control system, a flight control system, a data processing system, etc., wherein: The flying platform is the carrier of the drone carrying the measurement task sensors. The commonly used flying platforms in measurement include fixed-wing platforms, multi-rotor platforms, helicopters, unmanned airships, etc.

[0031] The mission load is mainly used to obtain measurement data such as images and videos of the operation area, so as to obtain image data of the current hydropower project reservoir bank area. It consists of mission equipment, a stable platform, and a mission equipment control system. The mission equipment is used to collect image data; the stable platform is used to stabilize the sensor equipment and correct the drift angle; the mission equipment control system is used to control the focus, exposure time and exposure interval of the mission equipment according to the received position, speed, altitude, heading, attitude angle of the drone and the set aerial photography scale and overlap data, and control the stable platform. Common mission equipment mainly includes high-resolution optical cameras, infrared sensors, oblique photography cameras, video cameras, etc. The main function of the stable platform is to stabilize the sensor equipment and correct the drift angle to ensure high-quality measurement data. By setting the control parameters of the flight control system, the attitude angle control accuracy of the drone during level flight and photography along the survey line meets the accuracy indicators of conventional measurement tasks. Commonly used stable platforms are three-axis and single-axis. The mission equipment control system controls the camera focus, exposure time and exposure interval, and controls the stable platform based on the received data such as the drone's position, speed, altitude, heading, attitude angle, and the set aerial photography scale and overlap.

[0032] The purpose of the flight control system is to achieve UAV flight control and mission load management, including two parts: the airborne flight control system and the ground control system. The airborne flight control system consists of an attitude gyro, a magnetic heading sensor, a flight control computer, a navigation and positioning device, a power management system, etc. It can achieve precise control of flight attitude, altitude, speed, heading, and route, and has two modes: autonomous flight and automatic flight. The system can add or remove some typical modules according to mission requirements, and has the characteristics of easy implementation of redundancy technology and fault isolation. The ground control system is used to transmit the status parameters of the UAV and remote sensing equipment in real time, and can achieve real-time control of the UAV photogrammetry system, so that ground personnel can control the information of the UAV and remote sensing equipment, and store all command information for review over time. It mainly consists of a command decoder, a modulator, a receiver, a transmitter, an antenna, a microcomputer, and a display.

[0033] The data processing system is mainly used to process the acquired drone attitude information (POS data) and the original data of the mission payload to obtain different types of graphic data products. Specifically, after POS data processing, format conversion and preprocessing, different types of data products such as orthophotos, digital line maps, emergency thematic maps, etc. are generated. After information extraction, decision support is provided for disaster monitoring, digital city construction, cultural heritage protection, engineering monitoring, and national geographic surveys.

[0034] A series of analysis and processing are performed on the multiple images collected by the UAV photogrammetry system, such as stitching, aerial triangulation, orthorectification, mosaic fusion, etc., and a three-dimensional real-scene model of the current reservoir area is established using the processed images. The geological disasters in the current reservoir area are then determined through identification and annotation by interpretation software.

[0035] Stitching multiple images collected by the drone photogrammetry system means that only rough POS data is used before the multiple images collected by the drone are triangulated, and the images are matched and quickly stitched according to the characteristics between the images without introducing control points, so as to achieve the purpose of quickly generating rough orthophotos. The main feature of this stitching process is that it does not require the measurement of a large number of control points for triangulation, and directly and quickly generates rough orthophotos that can be used. It can meet the needs of survey and design, emergency mapping, etc. that need to quickly obtain high-resolution orthophotos.

[0036] In an embodiment of the present invention, the main process steps for stitching multiple images collected by a drone are as follows: (1) Parameter settings: including camera parameter settings, flight strip information, projection reference settings, POS data and image data format settings.

[0037] (2) Data preprocessing: including image distortion correction and creation of image pyramid.

[0038] (3) Connection point extraction: Based on the approximate POS data, the image feature matching algorithm is used to automatically extract the connection points of the survey area images, and the matching points with large vertical parallax are eliminated. The preliminary geographic coordinates of the same-name points are calculated based on the approximate exterior orientation 70 elements obtained by the global positioning system GNSS and the inertial sensor IMU, so that the various models can be connected on this basis.

[0039] (4) Fast stitching: The orientation parameters are combined with the rough DTM (Digital Elevation Model) generated during the image matching process to correct and stitch the image to obtain a fast orthophoto map of the survey area. While stitching the images, the image coordinates are replaced by geographic coordinates through image resampling, so that the entire image has coordinate values ​​consistent with GNSS.

[0040] Aerial triangulation refers to the use of photogrammetric analysis to determine the exterior orientation elements of all images in the area. The method is to use the image and object space coordinates of a small number of control points to solve the coordinates of unknown points, so that the number of known points in each stereo model increases by more than four, and then use these known points to solve the exterior orientation elements of all images.

[0041] Orthorectification refers to the use of DEM data to eliminate image projection errors caused by imaging methods and terrain undulations. Projection errors refer to the displacement of image points caused by terrain undulations. The accuracy of orthorectification depends largely on the accuracy of DEM. The image is divided into many small areas, and digital differential correction (transformation or mapping) is performed one by one. According to the digital ground model, the coordinates are solved using the corresponding image equation. Control points can be added to combine with DEM for more sophisticated orthorectification. The images encrypted by aerial triangulation and the DEM generated after point cloud classification are imported into the corresponding software. The DEM needs to cover the image area, perform orthorectification of the image, and generate a single image after orthorectification.

[0042] Mosaic fusion refers to the process of stitching together multiple radiometrically corrected images with overlapping areas taken under the same or different imaging conditions into a complete image through digital image mosaicking technology.

[0043] After the processing of multiple images collected by the drone is completed, the processed images are obtained, and the processed images are used to construct a three-dimensional real scene model of the current reservoir area. In specific implementation, the embodiment of the present invention uses Context Capture oblique photography post-processing software, first analyzes the acquired processed images, excludes defective images, ensures that the data used for three-dimensional reconstruction is complete and correct, and uses three-dimensional construction software to use the remaining images to construct a three-dimensional real scene model of the current reservoir area.

[0044] Step S200: Identify and mark geological disaster risk points in the three-dimensional real-scene model of the current reservoir area to determine each geological disaster risk point.

[0045] After constructing the three-dimensional real-scene model of the current reservoir area through the above steps, the EarthSurvey software platform is used to identify and mark the geological disaster risk points in the three-dimensional real-scene model, and obtain various geological disaster risk points to prevent and control the reservoir bank area of ​​the current hydropower project.

[0046] Step S300: Perform dynamic identification during the water storage period to determine the target geological disaster risk point among the various geological disaster risk points.

[0047] Different types of geological disasters have different characteristics, for example: Landslide geological disasters: The general interpretation features of typical landslides on the 3D real-life model include the plane morphology of dustpan-shaped (tongue-shaped, irregular, etc.), landslide walls, landslide steps, landslide tongues, landslide cracks, landslide drums, closed injection areas, etc. In addition to local identification, it should also be judged from a large range of geomorphological morphology. For example, landslides are mostly developed on gentle slopes in canyons, shady slopes in watersheds, and at the intersection of main and branch gullies and their sources where the erosion base level changes sharply.

[0048] Collapse geological disaster: The surface of the collapsed accumulation body is mostly uniform grayish white to light gray, and its color change varies due to the influence of the parent rock color. The color boundary is relatively clear, showing a sudden color boundary. The supply area, transportation area and accumulation area can be distinguished. The supply area can see uneven, shadowed cliffs and rocks. The slope is severely destructive, and the accumulation is mainly composed of blocks, gravel and rock debris, or contains a small amount of fine debris. There is no vegetation coverage or a small amount of vegetation growth. The longitudinal slope of the collapse is mostly straight or round, with sparse plants growing on the surface. And the body color is lighter and uniform, with a rough feeling and dark dot-like feeling, and the material composition is mainly gravel and large stones. When the collapse accumulation appears alone, its plane shape is mostly tongue-shaped, pear-shaped, etc., and the stable rock dimension is mostly a collapse skirt; its surface color is darker, with uneven color and spots; the longitudinal section is straight and concave, and the cross-section protrusion is not obvious. The collapse boundary is covered by vegetation and is not clear, which is a gradual transition state.

[0049] By monitoring the reservoir bank area of ​​the hydropower project in the early stage of water storage, possible disaster types can be identified and various geological disaster risk points can be determined. During the water storage period, dynamic identification can be carried out to identify specific disaster types and obtain target geological disaster risk points.

[0050] Among them, dynamic identification during the water storage period includes two parts: dynamic risk assessment of the reservoir area and detailed verification by drones, including: During the water storage period, the dynamic hazard assessment method is first used, that is, on the basis of the susceptibility zoning of the reservoir bank area's disaster background conditions, the destructive factors caused by the impact of water level changes are considered to predict the hazard of the reservoir area, predicting which slopes are extremely high-risk slopes and which slopes are high-risk slopes. For slopes of different hazards, the degree of attention is different, focusing on extremely high-risk and high-risk slopes, and appropriately reducing the degree of attention for medium-risk and low-risk slopes. The focus of the work can be better adjusted to identify geological hazards on extremely high-risk and high-risk slopes.

[0051] Subsequently, drones were used for detailed verification, that is, conventional flights were used to conduct detailed verification of the reservoir area. For slopes with large terrain undulations, the terrain-simulating flight method was used to compensate for the image inaccuracies caused by conventional flights, and the deformation areas and deformation values ​​were accurately identified. For high and steep slopes, close-up photogrammetry technology was used to highly restore the characteristics of the fine structure of the surface and rock mass, and accurately extract and identify the rock mass structural surface.

[0052] For the above steps, some areas in the reservoir area have large height differences, and terrain factors have a great impact on the accuracy of drone photogrammetry. The reservoir area has a height difference of hundreds of meters. If it can only fly at a certain altitude, it is difficult to guarantee both the image quality and overlap. If the aircraft can fly at a relatively constant altitude according to the undulations of the ground, it can not only ensure the safety of the aircraft but also greatly improve the image quality. Therefore, in order to obtain high-precision images in areas with large height differences in the reservoir area, specific areas are selected in the reservoir area to carry out drone terrain simulation flights, and the route settings are as follows: Figure 3 The distance from each point on the route to the ground is a fixed height H.

[0053] Its working principle is that during the oblique photogrammetry operation in the landslide area, the drone sets the aerial survey altitude corresponding to the terrain altitude of the known landslide body in advance, so that the drone maintains a constant height difference with the landslide surface during flight. The drone's "terrain-like flight" technology is well suited for oblique photogrammetry under the terrain conditions of the landslide area. According to different landslide survey area terrain aerial survey software, it will automatically generate a variable height route corresponding to the altitude of the landslide body, keep the resolution of the landslide surface image consistent, and thus form a more realistic three-dimensional model of the landslide area.

[0054] The main difference between the operation process of terrain-simulating UAV photogrammetry and traditional aerial photography is in route planning. Route planning and design requires existing terrain data as support for route calculation. During the operation, the UAV sets a fixed height relative to the known three-dimensional terrain to keep a constant height difference between the aircraft and the target object. At present, there are two main ways to achieve terrain-simulating flight: a. Self-made digital surface model (DSM) data, first fly once in the study area using the 2D orthophoto method, use Pix4d and other aerial triangulation software to generate the DSM of the study area, and then import the two DSM files (including tif and tfw) into the remote controller. The DSM generated by this method is relatively fine and can achieve better terrain simulation effects, but the workload is large, and for areas with large height differences in mountainous areas, safety issues are difficult to guarantee during the first flight.

[0055] b. Use the existing digital elevation model (DEM) to replace DSM. Compared with DSM data, DEM data lacks elevation information such as vegetation and buildings. Therefore, when using DEM to replace DSM for terrain simulation flight, pay attention to the height of vegetation, buildings, high-voltage power towers and other structures in the flight area.

[0056] After studying specific areas, it was found that using drones to simulate terrain to monitor the surface displacement of large landslides and identify other disaster risk points is more effective than conventional flights. The three-dimensional model established based on the image data collected by drones simulated terrain flight can more accurately interpret and label disaster risks in the later stage, and the identification effect is better.

[0057] Based on the same inventive concept, the embodiment of the present invention also provides a large-scale hydropower project reservoir bank geological disaster identification device, such as Figure 4 As shown, the device includes: a memory 401, a processor 402, and a computer program 403 stored in the memory 401 and running on the processor 402, wherein when the processor 402 executes the computer program 403, the system can execute any of the large-scale hydropower project reservoir bank geological disaster identification methods introduced above.

[0058] It should be noted that: the device provided in the above embodiment is only illustrated by the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the computer device is divided into different functional modules to complete all or part of the functions described above. In addition, since the device provided in this embodiment and the method for identifying geological hazards on the bank of a large hydropower project provided in the above embodiment belong to the same concept, the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0059] It should be noted that the above-described embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A method for identifying geological hazards on the reservoir bank of a large hydropower project, characterized in that: The following steps are involved: In the early stage of water storage, the UAV photogrammetry system is controlled to collect multiple images of the reservoir bank area of ​​the current hydropower project, the multiple images are analyzed and processed, and a three-dimensional real scene model of the current reservoir area is constructed using the processed images; Identify and mark the geological disaster risk points in the 3D real-life model of the current reservoir area and determine each geological disaster risk point; Dynamic identification is performed during the water storage period to determine the target geological disaster risk points among the various geological disaster risk points.

2. A method for identifying geological hazards on the reservoir bank of a large hydropower project according to claim 1, characterized in that: Analyzing and processing the multiple images, including: The multiple images are sequentially stitched, aerially triangulated, orthorectified, and mosaicked to obtain a processed image.

3. A method for identifying geological hazards on the reservoir bank of a large hydropower project according to claim 2, characterized in that: The aerial triangulation includes determining the exterior orientation elements of all images in the area using photogrammetric analysis.

4. A method for identifying geological hazards on the reservoir bank of a large hydropower project according to claim 2, characterized in that: The orthorectification includes: The image is divided into multiple sub-areas, and digital differential correction is performed one by one. According to the digital ground model, the coordinates are solved using the corresponding image equations. Import the aerial triangulated images and the DEM generated after point cloud classification into the corresponding software. The DEM needs to cover the image area, perform orthorectification on the image, and generate a single image after orthorectification.

5. A method for identifying geological hazards on the reservoir bank of a large hydropower project according to claim 2, characterized in that: The mosaic fusion comprises: The digital image mosaic technology is used to stitch together multiple orthorectified images with overlapping areas taken under the same or different imaging conditions into a complete image.

6. A method for identifying geological hazards on the reservoir bank of a large hydropower project according to claim 1, characterized in that: The three-dimensional real scene model of the current reservoir area is constructed using the processed images, including: Context Capture oblique photography post-processing software was used to analyze the acquired processed images and exclude defective images; Use the remaining images to construct a three-dimensional real-life model of the current reservoir area.

7. A method for identifying geological hazards on the reservoir bank of a large hydropower project according to claim 1, characterized in that: Identify and mark the geological disaster risk points in the 3D real-life model of the current reservoir area, and determine each geological disaster risk point, including: The EarthSurvey software platform is used to identify and mark the geological disaster risk points in the three-dimensional real-scene model to obtain each geological disaster risk point.

8. A method for identifying geological hazards on the reservoir bank of a large hydropower project according to claim 1, characterized in that: Dynamic identification is performed during the water storage period to determine the target geological disaster risk points among the various geological disaster risk points, including: Conduct dynamic risk assessment of the reservoir area during the impoundment period; Based on the results of the dynamic hazard assessment of the reservoir area, detailed drone verification is carried out to determine the target geological disaster risk points among the various geological disaster risk points.

9. A method for identifying geological hazards on the reservoir bank of a large hydropower project according to claim 8, characterized in that: Conduct dynamic hazard assessment of the reservoir area, including identification of extremely high-risk slopes and high-risk slopes.

10. A device for identifying geological disasters on the bank of a large hydropower project, characterized in that: It comprises a memory, a processor and an executable computer program stored in the memory and runnable on the processor, wherein when the processor executes the computer program, a method for identifying geological hazards on the reservoir bank of a large hydropower project as described in any one of claims 1 to 9 is executed.

Images